As an increasing number of randomized controlled trials demonstrate the efficacy of particular therapies for specific problems, clinical research has begun to focus more intensely on questions of therapeutic mechanism. How do specific interventions change clients' thoughts, behaviors, and emotions and lead to greater mental health and well-being? The goal of the present research is to develop innovative methods of studying psychotherapy mechanisms through the use of two computational, language analysis programs, Linguistic Inquiry and Word Count (LIWC; Pennebaker & Francis, 1996) and Latent Semantic Analysis (LSA; Landauer & Dumais, 1997). We propose to apply and validate LIWC and LSA using transcripts of couple therapy from the Acceptance and Change in Marital Therapy study. Following analyses to assess the convergent and divergent validity of the language programs using already collected self-report and behavioral observation data, we will use the two programs to test theory-driven hypotheses of therapeutic mechanism that use the verbatim language of therapy as their source data. In addition, because of the nature of the resulting data (i.e., complex, multivariate time-series on a relatively small number of couples), we plan a simulation study comparing traditional, maximum likelihood estimation to two alternative methods of conducting mixed-effects analyses (also called hierarchical linear models and multilevel models) with small sample sizes: nonparametric bootstrap and Bayesian methods. The results of our study would have general application to the study of therapeutic mechanism and complex mixed-effects analyses with small sample-sizes. The research results will have direct relevance to the creation, revision, and streamlining of psychotherapies leading to more effective and less expensive psychotherapy and would also impact the training of therapists. [unreadable] [unreadable]